Swapping a classical embedding for an IQP quantum circuit embedding improved LLM-based table imputation in simulations, but the gains are reported without code, data, or error bars.
Improving the perfor- mance of short-term load forecast using a hybrid artificial neural network and artificial bee colony algorithm,
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Quantum-Accelerated Neural Imputation with Large Language Models (LLMs)
Swapping a classical embedding for an IQP quantum circuit embedding improved LLM-based table imputation in simulations, but the gains are reported without code, data, or error bars.